{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 存款利率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df1 = ts.get_deposit_rate()\n",
    "# df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定活两便(定期)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(半年)</td>\n",
       "      <td>1.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(二年)</td>\n",
       "      <td>2.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(三个月)</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(三年)</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(五年)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>定期存款整存整取(一年)</td>\n",
       "      <td>1.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>活期存款(不定期)</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>零存整取、整存零取、存本取息定期存款(三年)</td>\n",
       "      <td>1.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>零存整取、整存零取、存本取息定期存款(五年)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>零存整取、整存零取、存本取息定期存款(一年)</td>\n",
       "      <td>1.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date            deposit_type  rate\n",
       "0   2015-10-24                定活两便(定期)    --\n",
       "1   2015-10-24            定期存款整存整取(半年)  1.30\n",
       "2   2015-10-24            定期存款整存整取(二年)  2.10\n",
       "3   2015-10-24           定期存款整存整取(三个月)  1.10\n",
       "4   2015-10-24            定期存款整存整取(三年)  2.75\n",
       "5   2015-10-24            定期存款整存整取(五年)    --\n",
       "6   2015-10-24            定期存款整存整取(一年)  1.50\n",
       "7   2015-10-24               活期存款(不定期)  0.35\n",
       "8   2015-10-24  零存整取、整存零取、存本取息定期存款(三年)  1.30\n",
       "9   2015-10-24  零存整取、整存零取、存本取息定期存款(五年)    --\n",
       "10  2015-10-24  零存整取、整存零取、存本取息定期存款(一年)  1.10"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.loc[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- date：变动日期；  \n",
    "- deposit_type：存款种类；  \n",
    "- rate：利率(%)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 贷款利率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>loan_type</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>短期贷款(六个月以内)</td>\n",
       "      <td>4.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>短期贷款(六个月至一年)</td>\n",
       "      <td>4.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>中长期贷款(三至五年)</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>中长期贷款(五年以上)</td>\n",
       "      <td>4.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>中长期贷款(一至三年)</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>贴现(贴现)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>优惠贷款(扶贫贴息贷款)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>优惠贷款(老少边穷发展经济贷款)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>优惠贷款(民政部门福利工厂贷款)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>优惠贷款(民族贸易及民族用品生产贷款)</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date            loan_type  rate\n",
       "0  2015-10-24          短期贷款(六个月以内)  4.35\n",
       "1  2015-10-24         短期贷款(六个月至一年)  4.35\n",
       "2  2015-10-24          中长期贷款(三至五年)  4.75\n",
       "3  2015-10-24          中长期贷款(五年以上)  4.90\n",
       "4  2015-10-24          中长期贷款(一至三年)  4.75\n",
       "5  2015-10-24               贴现(贴现)    --\n",
       "6  2015-10-24         优惠贷款(扶贫贴息贷款)    --\n",
       "7  2015-10-24     优惠贷款(老少边穷发展经济贷款)    --\n",
       "8  2015-10-24     优惠贷款(民政部门福利工厂贷款)    --\n",
       "9  2015-10-24  优惠贷款(民族贸易及民族用品生产贷款)    --"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df2 = ts.get_loan_rate()\n",
    "df2.loc[0:9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'9.90'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['rate'].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- date：变动日期；  \n",
    "- loan_type：贷款种类；  \n",
    "- rate：利率(%)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 存款准备金率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>before</th>\n",
       "      <th>now</th>\n",
       "      <th>changed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-25</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>14.00</td>\n",
       "      <td>13.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-10-15</td>\n",
       "      <td>15.00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-07-05</td>\n",
       "      <td>15.50</td>\n",
       "      <td>15.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>16.50</td>\n",
       "      <td>15.5</td>\n",
       "      <td>-1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016-03-01</td>\n",
       "      <td>17.00</td>\n",
       "      <td>16.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2015-10-24</td>\n",
       "      <td>17.50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015-09-06</td>\n",
       "      <td>18.00</td>\n",
       "      <td>17.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015-06-28</td>\n",
       "      <td>18.50</td>\n",
       "      <td>18.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2015-04-20</td>\n",
       "      <td>19.50</td>\n",
       "      <td>18.5</td>\n",
       "      <td>-1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2015-02-05</td>\n",
       "      <td>20.00</td>\n",
       "      <td>19.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2012-05-18</td>\n",
       "      <td>20.50</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2012-02-24</td>\n",
       "      <td>21.00</td>\n",
       "      <td>20.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>21.50</td>\n",
       "      <td>21.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2011-06-20</td>\n",
       "      <td>21.00</td>\n",
       "      <td>21.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2011-05-18</td>\n",
       "      <td>20.50</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2011-04-21</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2011-03-25</td>\n",
       "      <td>19.50</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2011-02-24</td>\n",
       "      <td>19.00</td>\n",
       "      <td>19.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2011-01-20</td>\n",
       "      <td>18.50</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2010-12-20</td>\n",
       "      <td>18.00</td>\n",
       "      <td>18.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2010-11-29</td>\n",
       "      <td>17.50</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2010-11-16</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2010-05-10</td>\n",
       "      <td>16.50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2010-02-25</td>\n",
       "      <td>16.00</td>\n",
       "      <td>16.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2010-01-18</td>\n",
       "      <td>15.50</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2008-12-25</td>\n",
       "      <td>16.00</td>\n",
       "      <td>15.5</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2008-12-05</td>\n",
       "      <td>17.00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>-1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2008-10-15</td>\n",
       "      <td>17.50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>-0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2008-09-25</td>\n",
       "      <td>17.50</td>\n",
       "      <td>17.5</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2008-06-25</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2008-06-15</td>\n",
       "      <td>16.50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2008-05-20</td>\n",
       "      <td>16.00</td>\n",
       "      <td>16.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2008-04-25</td>\n",
       "      <td>15.50</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2008-03-25</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2008-01-25</td>\n",
       "      <td>14.50</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2007-12-25</td>\n",
       "      <td>13.50</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2007-11-26</td>\n",
       "      <td>13.00</td>\n",
       "      <td>13.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2007-10-25</td>\n",
       "      <td>12.50</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2007-09-25</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2007-08-15</td>\n",
       "      <td>11.50</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2007-06-05</td>\n",
       "      <td>11.00</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2007-05-15</td>\n",
       "      <td>10.50</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2007-04-16</td>\n",
       "      <td>10.00</td>\n",
       "      <td>10.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2007-02-25</td>\n",
       "      <td>9.50</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2007-01-15</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2006-11-15</td>\n",
       "      <td>8.50</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2006-08-15</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2006-07-05</td>\n",
       "      <td>7.50</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2004-04-25</td>\n",
       "      <td>7.00</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2003-09-21</td>\n",
       "      <td>6.00</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1999-11-21</td>\n",
       "      <td>8.00</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1998-03-21</td>\n",
       "      <td>13.00</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-5.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>1988-09-30</td>\n",
       "      <td>12.00</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>1987-12-31</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>1985-12-31</td>\n",
       "      <td>--</td>\n",
       "      <td>10.0</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date before   now changed\n",
       "0   2019-01-25  13.50  13.0   -0.50\n",
       "1   2019-01-15  14.00  13.5   -0.50\n",
       "2   2018-10-15  15.00  14.0   -1.00\n",
       "3   2018-07-05  15.50  15.0   -0.50\n",
       "4   2018-04-25  16.50  15.5   -1.00\n",
       "5   2016-03-01  17.00  16.5   -0.50\n",
       "6   2015-10-24  17.50  17.0   -0.50\n",
       "7   2015-09-06  18.00  17.5   -0.50\n",
       "8   2015-06-28  18.50  18.0   -0.50\n",
       "9   2015-04-20  19.50  18.5   -1.00\n",
       "10  2015-02-05  20.00  19.5   -0.50\n",
       "11  2012-05-18  20.50  20.0   -0.50\n",
       "12  2012-02-24  21.00  20.5   -0.50\n",
       "13  2011-12-05  21.50  21.0   -0.50\n",
       "14  2011-06-20  21.00  21.5    0.50\n",
       "15  2011-05-18  20.50  21.0    0.50\n",
       "16  2011-04-21  20.00  20.5    0.50\n",
       "17  2011-03-25  19.50  20.0    0.50\n",
       "18  2011-02-24  19.00  19.5    0.50\n",
       "19  2011-01-20  18.50  19.0    0.50\n",
       "20  2010-12-20  18.00  18.5    0.50\n",
       "21  2010-11-29  17.50  18.0    0.50\n",
       "22  2010-11-16  17.00  17.5    0.50\n",
       "23  2010-05-10  16.50  17.0    0.50\n",
       "24  2010-02-25  16.00  16.5    0.50\n",
       "25  2010-01-18  15.50  16.0    0.50\n",
       "26  2008-12-25  16.00  15.5   -0.50\n",
       "27  2008-12-05  17.00  16.0   -1.00\n",
       "28  2008-10-15  17.50  17.0   -0.50\n",
       "29  2008-09-25  17.50  17.5    0.00\n",
       "30  2008-06-25  17.00  17.5    0.50\n",
       "31  2008-06-15  16.50  17.0    0.50\n",
       "32  2008-05-20  16.00  16.5    0.50\n",
       "33  2008-04-25  15.50  16.0    0.50\n",
       "34  2008-03-25  15.00  15.5    0.50\n",
       "35  2008-01-25  14.50  15.0    0.50\n",
       "36  2007-12-25  13.50  14.5    1.00\n",
       "37  2007-11-26  13.00  13.5    0.50\n",
       "38  2007-10-25  12.50  13.0    0.50\n",
       "39  2007-09-25  12.00  12.5    0.50\n",
       "40  2007-08-15  11.50  12.0    0.50\n",
       "41  2007-06-05  11.00  11.5    0.50\n",
       "42  2007-05-15  10.50  11.0    0.50\n",
       "43  2007-04-16  10.00  10.5    0.50\n",
       "44  2007-02-25   9.50  10.0    0.50\n",
       "45  2007-01-15   9.00   9.5    0.50\n",
       "46  2006-11-15   8.50   9.0    0.50\n",
       "47  2006-08-15   8.00   8.5    0.50\n",
       "48  2006-07-05   7.50   8.0    0.50\n",
       "49  2004-04-25   7.00   7.5    0.50\n",
       "50  2003-09-21   6.00   7.0    1.00\n",
       "51  1999-11-21   8.00   6.0   -2.00\n",
       "52  1998-03-21  13.00   8.0   -5.00\n",
       "53  1988-09-30  12.00  13.0    1.00\n",
       "54  1987-12-31  10.00  12.0    2.00\n",
       "55  1985-12-31     --  10.0      --"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "import pandas as pd\n",
    "\n",
    "df3 = ts.get_rrr()\n",
    "\n",
    "# 将数据存储为excel文件\n",
    "df3.to_excel(r'./dataFiles/rrr.xlsx')\n",
    "\n",
    "df3_excel = pd.read_excel(r'./dataFiles/rrr.xlsx',encoding='ansi')\n",
    "df3_excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21.5"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 对指定列求最大值\n",
    "df3_excel['now'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'9.50'"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 对指定列求最大值\n",
    "df3_excel['before'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date       2019-01-25\n",
       "before           9.50\n",
       "now              21.5\n",
       "changed          2.00\n",
       "dtype: object"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3_excel.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 货币供应量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>m2</th>\n",
       "      <th>m2_yoy</th>\n",
       "      <th>m1</th>\n",
       "      <th>m1_yoy</th>\n",
       "      <th>m0</th>\n",
       "      <th>m0_yoy</th>\n",
       "      <th>cd</th>\n",
       "      <th>cd_yoy</th>\n",
       "      <th>qm</th>\n",
       "      <th>qm_yoy</th>\n",
       "      <th>ftd</th>\n",
       "      <th>ftd_yoy</th>\n",
       "      <th>sd</th>\n",
       "      <th>sd_yoy</th>\n",
       "      <th>rests</th>\n",
       "      <th>rests_yoy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019.6</td>\n",
       "      <td>1921360.19</td>\n",
       "      <td>8.50</td>\n",
       "      <td>567696.18</td>\n",
       "      <td>4.40</td>\n",
       "      <td>72580.96</td>\n",
       "      <td>4.30</td>\n",
       "      <td>495115.22</td>\n",
       "      <td>--</td>\n",
       "      <td>1353664.01</td>\n",
       "      <td>--</td>\n",
       "      <td>362162.76</td>\n",
       "      <td>--</td>\n",
       "      <td>790201.11</td>\n",
       "      <td>--</td>\n",
       "      <td>201300.14</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019.5</td>\n",
       "      <td>1891153.70</td>\n",
       "      <td>8.50</td>\n",
       "      <td>544355.64</td>\n",
       "      <td>3.40</td>\n",
       "      <td>72798.46</td>\n",
       "      <td>4.30</td>\n",
       "      <td>471557.18</td>\n",
       "      <td>--</td>\n",
       "      <td>1346798.06</td>\n",
       "      <td>--</td>\n",
       "      <td>364890.78</td>\n",
       "      <td>--</td>\n",
       "      <td>778725.61</td>\n",
       "      <td>--</td>\n",
       "      <td>203181.67</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019.4</td>\n",
       "      <td>1884670.33</td>\n",
       "      <td>8.50</td>\n",
       "      <td>540614.60</td>\n",
       "      <td>2.90</td>\n",
       "      <td>73965.76</td>\n",
       "      <td>3.50</td>\n",
       "      <td>466648.84</td>\n",
       "      <td>--</td>\n",
       "      <td>1344055.72</td>\n",
       "      <td>--</td>\n",
       "      <td>365304.79</td>\n",
       "      <td>--</td>\n",
       "      <td>776276.48</td>\n",
       "      <td>--</td>\n",
       "      <td>202474.45</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019.3</td>\n",
       "      <td>1889412.14</td>\n",
       "      <td>8.60</td>\n",
       "      <td>547575.54</td>\n",
       "      <td>4.60</td>\n",
       "      <td>74941.58</td>\n",
       "      <td>3.10</td>\n",
       "      <td>472633.97</td>\n",
       "      <td>--</td>\n",
       "      <td>1341836.59</td>\n",
       "      <td>--</td>\n",
       "      <td>359015.48</td>\n",
       "      <td>--</td>\n",
       "      <td>782606.12</td>\n",
       "      <td>--</td>\n",
       "      <td>200214.99</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019.2</td>\n",
       "      <td>1867427.45</td>\n",
       "      <td>8.00</td>\n",
       "      <td>527190.48</td>\n",
       "      <td>2.00</td>\n",
       "      <td>79484.72</td>\n",
       "      <td>-2.40</td>\n",
       "      <td>447705.76</td>\n",
       "      <td>--</td>\n",
       "      <td>1340236.97</td>\n",
       "      <td>--</td>\n",
       "      <td>356710.05</td>\n",
       "      <td>--</td>\n",
       "      <td>773741.13</td>\n",
       "      <td>--</td>\n",
       "      <td>209785.79</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019.1</td>\n",
       "      <td>1865935.33</td>\n",
       "      <td>8.40</td>\n",
       "      <td>545638.46</td>\n",
       "      <td>0.40</td>\n",
       "      <td>87470.62</td>\n",
       "      <td>17.20</td>\n",
       "      <td>458167.84</td>\n",
       "      <td>--</td>\n",
       "      <td>1320296.87</td>\n",
       "      <td>--</td>\n",
       "      <td>355604.75</td>\n",
       "      <td>--</td>\n",
       "      <td>760391.93</td>\n",
       "      <td>--</td>\n",
       "      <td>204300.19</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    month          m2 m2_yoy         m1 m1_yoy        m0 m0_yoy         cd  \\\n",
       "0  2019.6  1921360.19   8.50  567696.18   4.40  72580.96   4.30  495115.22   \n",
       "1  2019.5  1891153.70   8.50  544355.64   3.40  72798.46   4.30  471557.18   \n",
       "2  2019.4  1884670.33   8.50  540614.60   2.90  73965.76   3.50  466648.84   \n",
       "3  2019.3  1889412.14   8.60  547575.54   4.60  74941.58   3.10  472633.97   \n",
       "4  2019.2  1867427.45   8.00  527190.48   2.00  79484.72  -2.40  447705.76   \n",
       "5  2019.1  1865935.33   8.40  545638.46   0.40  87470.62  17.20  458167.84   \n",
       "\n",
       "  cd_yoy          qm qm_yoy        ftd ftd_yoy         sd sd_yoy      rests  \\\n",
       "0     --  1353664.01     --  362162.76      --  790201.11     --  201300.14   \n",
       "1     --  1346798.06     --  364890.78      --  778725.61     --  203181.67   \n",
       "2     --  1344055.72     --  365304.79      --  776276.48     --  202474.45   \n",
       "3     --  1341836.59     --  359015.48      --  782606.12     --  200214.99   \n",
       "4     --  1340236.97     --  356710.05      --  773741.13     --  209785.79   \n",
       "5     --  1320296.87     --  355604.75      --  760391.93     --  204300.19   \n",
       "\n",
       "  rests_yoy  \n",
       "0        --  \n",
       "1        --  \n",
       "2        --  \n",
       "3        --  \n",
       "4        --  \n",
       "5        --  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df4 = ts.get_money_supply()\n",
    "df4.loc[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- month：统计时间\n",
    "- m2：广义货币（流通中现金+活期存款+定期存款+储蓄存款）（亿元）；\n",
    "- m2_yoy：广义货币同比增长（%）；\n",
    "- m1：狭义货币（亿元）；\n",
    "- m1_yoy：狭义货币同比增长（%）；\n",
    "- m0：流通中现金（亿元）；\n",
    "- m0_yoy：流通中现金同比增长（%）；\n",
    "- cd：活期存款（亿元）；\n",
    "- cd_yoy：活期存款同比增长（%）；\n",
    "- qm：准货币（亿元）；\n",
    "- qm_yoy：准货币同比增长（%）；\n",
    "- ftd：定期存款（亿元）；\n",
    "- ftd_yoy：定期存款同比增长（%）；\n",
    "- sd：储蓄存款（亿元）；\n",
    "- sd_yoy：储蓄存款同比增长（%）；\n",
    "- rests：其他存款（亿元）；\n",
    "- rests_yoy：其他存款同比增长（%）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 货币供应量（年底余额）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>m2</th>\n",
       "      <th>m1</th>\n",
       "      <th>m0</th>\n",
       "      <th>cd</th>\n",
       "      <th>qm</th>\n",
       "      <th>ftd</th>\n",
       "      <th>sd</th>\n",
       "      <th>rests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>1826744.00</td>\n",
       "      <td>551686.00</td>\n",
       "      <td>73208.00</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>1690235.30</td>\n",
       "      <td>543790.10</td>\n",
       "      <td>70645.60</td>\n",
       "      <td>473144.50</td>\n",
       "      <td>1146445.20</td>\n",
       "      <td>320196.20</td>\n",
       "      <td>649341.50</td>\n",
       "      <td>176907.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>1550066.70</td>\n",
       "      <td>486557.20</td>\n",
       "      <td>68303.90</td>\n",
       "      <td>418253.40</td>\n",
       "      <td>1063509.40</td>\n",
       "      <td>307989.60</td>\n",
       "      <td>603504.20</td>\n",
       "      <td>152015.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>1392278.10</td>\n",
       "      <td>400953.40</td>\n",
       "      <td>63216.60</td>\n",
       "      <td>337736.90</td>\n",
       "      <td>991324.70</td>\n",
       "      <td>288240.70</td>\n",
       "      <td>552073.50</td>\n",
       "      <td>151010.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>1228374.80</td>\n",
       "      <td>348056.40</td>\n",
       "      <td>60259.50</td>\n",
       "      <td>287796.90</td>\n",
       "      <td>880318.40</td>\n",
       "      <td>264055.70</td>\n",
       "      <td>508878.10</td>\n",
       "      <td>107384.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>1106525.00</td>\n",
       "      <td>337291.10</td>\n",
       "      <td>58574.40</td>\n",
       "      <td>278716.60</td>\n",
       "      <td>769233.90</td>\n",
       "      <td>232696.60</td>\n",
       "      <td>467031.10</td>\n",
       "      <td>69506.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>974148.80</td>\n",
       "      <td>308664.20</td>\n",
       "      <td>54659.80</td>\n",
       "      <td>254004.50</td>\n",
       "      <td>665484.60</td>\n",
       "      <td>195940.10</td>\n",
       "      <td>411362.60</td>\n",
       "      <td>58181.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011</td>\n",
       "      <td>851590.90</td>\n",
       "      <td>289847.70</td>\n",
       "      <td>50748.50</td>\n",
       "      <td>239099.20</td>\n",
       "      <td>561743.20</td>\n",
       "      <td>166616.00</td>\n",
       "      <td>352797.50</td>\n",
       "      <td>42329.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>725851.80</td>\n",
       "      <td>266621.50</td>\n",
       "      <td>44628.20</td>\n",
       "      <td>221993.40</td>\n",
       "      <td>459230.30</td>\n",
       "      <td>105858.70</td>\n",
       "      <td>303302.50</td>\n",
       "      <td>50069.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009</td>\n",
       "      <td>610224.50</td>\n",
       "      <td>221445.80</td>\n",
       "      <td>38247.00</td>\n",
       "      <td>183198.80</td>\n",
       "      <td>388778.70</td>\n",
       "      <td>84819.50</td>\n",
       "      <td>260752.70</td>\n",
       "      <td>43206.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year          m2         m1        m0         cd          qm        ftd  \\\n",
       "0  2018  1826744.00  551686.00  73208.00         --          --         --   \n",
       "1  2017  1690235.30  543790.10  70645.60  473144.50  1146445.20  320196.20   \n",
       "2  2016  1550066.70  486557.20  68303.90  418253.40  1063509.40  307989.60   \n",
       "3  2015  1392278.10  400953.40  63216.60  337736.90   991324.70  288240.70   \n",
       "4  2014  1228374.80  348056.40  60259.50  287796.90   880318.40  264055.70   \n",
       "5  2013  1106525.00  337291.10  58574.40  278716.60   769233.90  232696.60   \n",
       "6  2012   974148.80  308664.20  54659.80  254004.50   665484.60  195940.10   \n",
       "7  2011   851590.90  289847.70  50748.50  239099.20   561743.20  166616.00   \n",
       "8  2010   725851.80  266621.50  44628.20  221993.40   459230.30  105858.70   \n",
       "9  2009   610224.50  221445.80  38247.00  183198.80   388778.70   84819.50   \n",
       "\n",
       "          sd      rests  \n",
       "0         --         --  \n",
       "1  649341.50  176907.40  \n",
       "2  603504.20  152015.60  \n",
       "3  552073.50  151010.50  \n",
       "4  508878.10  107384.60  \n",
       "5  467031.10   69506.20  \n",
       "6  411362.60   58181.90  \n",
       "7  352797.50   42329.70  \n",
       "8  303302.50   50069.10  \n",
       "9  260752.70   43206.50  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df5 = ts.get_money_supply_bal()\n",
    "df5.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- month：统计时间\n",
    "- m2：广义货币（流通中现金+活期存款+定期存款+储蓄存款）（亿元）；\n",
    "- m1：狭义货币（亿元）；\n",
    "- m0：流通中现金（亿元）；\n",
    "- cd：活期存款（亿元）；\n",
    "- qm：准货币（亿元）；\n",
    "- ftd：定期存款（亿元）；\n",
    "- sd：储蓄存款（亿元）；\n",
    "- rests：其他存款（亿元）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 国内生产总值（年度）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>gdp</th>\n",
       "      <th>pc_gdp</th>\n",
       "      <th>gnp</th>\n",
       "      <th>pi</th>\n",
       "      <th>si</th>\n",
       "      <th>industry</th>\n",
       "      <th>cons_industry</th>\n",
       "      <th>ti</th>\n",
       "      <th>trans_industry</th>\n",
       "      <th>lbdy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>900309.5</td>\n",
       "      <td>64644.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64734.0</td>\n",
       "      <td>366000.90</td>\n",
       "      <td>305160.20</td>\n",
       "      <td>61808.00</td>\n",
       "      <td>469574.6</td>\n",
       "      <td>40550.20</td>\n",
       "      <td>100223.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>820754.3</td>\n",
       "      <td>59201.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62099.5</td>\n",
       "      <td>332742.70</td>\n",
       "      <td>278328.20</td>\n",
       "      <td>55313.80</td>\n",
       "      <td>425912.1</td>\n",
       "      <td>37172.60</td>\n",
       "      <td>92348.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>740060.8</td>\n",
       "      <td>53680.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60139.2</td>\n",
       "      <td>296547.70</td>\n",
       "      <td>247877.70</td>\n",
       "      <td>49702.90</td>\n",
       "      <td>383373.9</td>\n",
       "      <td>33058.80</td>\n",
       "      <td>84648.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>685992.9</td>\n",
       "      <td>50028.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57774.6</td>\n",
       "      <td>282040.30</td>\n",
       "      <td>236506.30</td>\n",
       "      <td>46626.70</td>\n",
       "      <td>346178.0</td>\n",
       "      <td>30487.80</td>\n",
       "      <td>78340.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>641280.6</td>\n",
       "      <td>47005.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55626.3</td>\n",
       "      <td>277571.80</td>\n",
       "      <td>233856.40</td>\n",
       "      <td>44880.50</td>\n",
       "      <td>308082.5</td>\n",
       "      <td>28500.90</td>\n",
       "      <td>73582.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>592963.2</td>\n",
       "      <td>43684.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53028.1</td>\n",
       "      <td>261956.10</td>\n",
       "      <td>210689.42</td>\n",
       "      <td>38995.00</td>\n",
       "      <td>277979.1</td>\n",
       "      <td>27282.93</td>\n",
       "      <td>66512.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>538580.0</td>\n",
       "      <td>39874.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49084.5</td>\n",
       "      <td>240200.40</td>\n",
       "      <td>199670.66</td>\n",
       "      <td>35491.34</td>\n",
       "      <td>244852.2</td>\n",
       "      <td>24660.00</td>\n",
       "      <td>60295.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011</td>\n",
       "      <td>487940.2</td>\n",
       "      <td>36302.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44781.4</td>\n",
       "      <td>223390.30</td>\n",
       "      <td>188470.15</td>\n",
       "      <td>31942.66</td>\n",
       "      <td>216120.0</td>\n",
       "      <td>22432.84</td>\n",
       "      <td>52903.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>401202.0</td>\n",
       "      <td>29992.0</td>\n",
       "      <td>403260.0</td>\n",
       "      <td>40533.6</td>\n",
       "      <td>187581.42</td>\n",
       "      <td>160867.01</td>\n",
       "      <td>26714.41</td>\n",
       "      <td>173087.0</td>\n",
       "      <td>18968.48</td>\n",
       "      <td>43814.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009</td>\n",
       "      <td>340902.8</td>\n",
       "      <td>25608.0</td>\n",
       "      <td>341401.5</td>\n",
       "      <td>35226.0</td>\n",
       "      <td>157638.80</td>\n",
       "      <td>135239.90</td>\n",
       "      <td>22398.80</td>\n",
       "      <td>148038.0</td>\n",
       "      <td>16727.10</td>\n",
       "      <td>36102.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year       gdp   pc_gdp       gnp       pi         si   industry  \\\n",
       "0  2018  900309.5  64644.0       NaN  64734.0  366000.90  305160.20   \n",
       "1  2017  820754.3  59201.0       NaN  62099.5  332742.70  278328.20   \n",
       "2  2016  740060.8  53680.0       NaN  60139.2  296547.70  247877.70   \n",
       "3  2015  685992.9  50028.0       NaN  57774.6  282040.30  236506.30   \n",
       "4  2014  641280.6  47005.0       NaN  55626.3  277571.80  233856.40   \n",
       "5  2013  592963.2  43684.0       NaN  53028.1  261956.10  210689.42   \n",
       "6  2012  538580.0  39874.0       NaN  49084.5  240200.40  199670.66   \n",
       "7  2011  487940.2  36302.0       NaN  44781.4  223390.30  188470.15   \n",
       "8  2010  401202.0  29992.0  403260.0  40533.6  187581.42  160867.01   \n",
       "9  2009  340902.8  25608.0  341401.5  35226.0  157638.80  135239.90   \n",
       "\n",
       "   cons_industry        ti  trans_industry       lbdy  \n",
       "0       61808.00  469574.6        40550.20  100223.80  \n",
       "1       55313.80  425912.1        37172.60   92348.20  \n",
       "2       49702.90  383373.9        33058.80   84648.80  \n",
       "3       46626.70  346178.0        30487.80   78340.40  \n",
       "4       44880.50  308082.5        28500.90   73582.00  \n",
       "5       38995.00  277979.1        27282.93   66512.40  \n",
       "6       35491.34  244852.2        24660.00   60295.21  \n",
       "7       31942.66  216120.0        22432.84   52903.35  \n",
       "8       26714.41  173087.0        18968.48   43814.55  \n",
       "9       22398.80  148038.0        16727.10   36102.70  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df6 = ts.get_gdp_year()\n",
    "df6.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- year：统计年度\n",
    "- gdp：国内生产总值（亿元）\n",
    "- pc_gdp：人均国内生产总值（元）\n",
    "- gnp：国民生产总值（亿元）\n",
    "- pi：第一产业（亿元）\n",
    "- si：第二产业（亿元）\n",
    "- industry：工业（亿元）\n",
    "- cons_industry：建筑业（亿元）\n",
    "- ti：第三产业（亿元）\n",
    "- trans_industry：交通运输仓储邮电通信业（亿元）\n",
    "- lbdy：批发零售贸易及餐饮业（亿元）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 国内生产总值（季度）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>quarter</th>\n",
       "      <th>gdp</th>\n",
       "      <th>gdp_yoy</th>\n",
       "      <th>pi</th>\n",
       "      <th>pi_yoy</th>\n",
       "      <th>si</th>\n",
       "      <th>si_yoy</th>\n",
       "      <th>ti</th>\n",
       "      <th>ti_yoy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019.2</td>\n",
       "      <td>450933.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>23207.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>179984.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>247743.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019.1</td>\n",
       "      <td>213432.8</td>\n",
       "      <td>6.4</td>\n",
       "      <td>8769.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>82346.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>122317.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.4</td>\n",
       "      <td>900309.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>64734.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>366001.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>469575.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.3</td>\n",
       "      <td>650899.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>42173.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>262953.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>345773.0</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.2</td>\n",
       "      <td>418961.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>22087.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>169299.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>227576.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018.1</td>\n",
       "      <td>198783.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>8904.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>77451.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>112428.0</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017.4</td>\n",
       "      <td>820754.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>62100.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>332743.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>425912.0</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017.3</td>\n",
       "      <td>593288.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>41229.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>238109.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>313951.0</td>\n",
       "      <td>7.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017.2</td>\n",
       "      <td>381490.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>21987.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>152987.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>206516.0</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2017.1</td>\n",
       "      <td>180683.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>8654.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>70005.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>102024.0</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  quarter       gdp  gdp_yoy       pi  pi_yoy        si  si_yoy        ti  \\\n",
       "0  2019.2  450933.0      6.3  23207.0     3.0  179984.0     5.8  247743.0   \n",
       "1  2019.1  213432.8      6.4   8769.0     2.7   82346.0     6.1  122317.0   \n",
       "2  2018.4  900309.0      6.6  64734.0     3.5  366001.0     5.8  469575.0   \n",
       "3  2018.3  650899.0      6.7  42173.0     3.4  262953.0     5.8  345773.0   \n",
       "4  2018.2  418961.0      6.8  22087.0     3.2  169299.0     6.1  227576.0   \n",
       "5  2018.1  198783.0      6.8   8904.0     3.2   77451.0     6.3  112428.0   \n",
       "6  2017.4  820754.0      6.8  62100.0     4.0  332743.0     5.9  425912.0   \n",
       "7  2017.3  593288.0      6.9  41229.0     3.7  238109.0     6.3  313951.0   \n",
       "8  2017.2  381490.0      6.9  21987.0     3.5  152987.0     6.4  206516.0   \n",
       "9  2017.1  180683.0      6.9   8654.0     3.0   70005.0     6.4  102024.0   \n",
       "\n",
       "   ti_yoy  \n",
       "0     7.0  \n",
       "1     7.0  \n",
       "2     7.6  \n",
       "3     7.7  \n",
       "4     7.6  \n",
       "5     7.5  \n",
       "6     7.9  \n",
       "7     7.8  \n",
       "8     7.7  \n",
       "9     7.7  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df7 = ts.get_gdp_quarter()\n",
    "df7.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- quarter：统计季度\n",
    "- gdp：国内生产总值（亿元）\n",
    "- gdp_yoy：国内生产总值同比增长（%）\n",
    "- pi：第一产业增加值（亿元）\n",
    "- pi_yoy：第一产业增加值同比增长（%）\n",
    "- si：第二产业增加值（亿元）\n",
    "- si_yoy：第二产业增加值同比增长；\n",
    "- ti：第三产业增加值（亿元）\n",
    "- ti_yoy：第三产业增加值同比增长。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三大需求对GDP的贡献"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>end_for</th>\n",
       "      <th>for_rate</th>\n",
       "      <th>asset_for</th>\n",
       "      <th>asset_rate</th>\n",
       "      <th>goods_for</th>\n",
       "      <th>goods_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>76.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>32.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-8.6</td>\n",
       "      <td>-0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>57.6</td>\n",
       "      <td>3.9</td>\n",
       "      <td>33.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>66.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-9.6</td>\n",
       "      <td>-0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>59.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>41.6</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>-0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>48.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>46.9</td>\n",
       "      <td>3.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>48.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>54.2</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-2.3</td>\n",
       "      <td>-0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>56.7</td>\n",
       "      <td>4.3</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011</td>\n",
       "      <td>61.9</td>\n",
       "      <td>5.9</td>\n",
       "      <td>46.2</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-8.1</td>\n",
       "      <td>-0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>46.9</td>\n",
       "      <td>4.8</td>\n",
       "      <td>66.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>-11.2</td>\n",
       "      <td>-1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009</td>\n",
       "      <td>56.1</td>\n",
       "      <td>5.3</td>\n",
       "      <td>86.5</td>\n",
       "      <td>8.1</td>\n",
       "      <td>-42.6</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  end_for  for_rate  asset_for  asset_rate  goods_for  goods_rate\n",
       "0  2018     76.2       5.0       32.4         2.2       -8.6        -0.6\n",
       "1  2017     57.6       3.9       33.8         2.3        8.6         0.6\n",
       "2  2016     66.5       4.5       43.1         2.9       -9.6        -0.7\n",
       "3  2015     59.7       4.1       41.6         2.9       -1.3        -0.1\n",
       "4  2014     48.8       3.6       46.9         3.4        4.3         0.3\n",
       "5  2013     48.2       3.6       54.2         4.3       -2.3        -0.1\n",
       "6  2012     56.7       4.3       42.0         3.4        1.7         0.2\n",
       "7  2011     61.9       5.9       46.2         4.4       -8.1        -0.8\n",
       "8  2010     46.9       4.8       66.0         7.1      -11.2        -1.3\n",
       "9  2009     56.1       5.3       86.5         8.1      -42.6        -4.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df8 = ts.get_gdp_for()\n",
    "df8.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- year：统计年度\n",
    "- end_for：最终消费支出贡献率（%）\n",
    "- for_rate：最终消费支出拉动（百分点）\n",
    "- asset_for：资产形成总额贡献率（%）\n",
    "- asset_rate：资本形成总额拉动（百分点）\n",
    "- goods_for：货物和服装净出口贡献率（%）\n",
    "- goods_rate：货物和服装净出口拉动（百分点）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三大产业对GDP的拉动"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>gdp_yoy</th>\n",
       "      <th>pi</th>\n",
       "      <th>si</th>\n",
       "      <th>industry</th>\n",
       "      <th>ti</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>6.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>7.8</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3.8</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>7.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011</td>\n",
       "      <td>9.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>10.6</td>\n",
       "      <td>0.4</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5.3</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009</td>\n",
       "      <td>9.4</td>\n",
       "      <td>0.4</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.8</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  gdp_yoy   pi   si  industry   ti\n",
       "0  2018      6.6  0.3  2.4       NaN  3.9\n",
       "1  2017      6.9  0.3  2.4       2.2  4.0\n",
       "2  2016      6.7  0.3  2.6       2.1  3.9\n",
       "3  2015      6.9  0.3  2.9       2.4  3.7\n",
       "4  2014      7.3  0.3  3.5       2.9  3.5\n",
       "5  2013      7.8  0.3  3.8       3.1  3.7\n",
       "6  2012      7.9  0.4  3.9       3.3  3.5\n",
       "7  2011      9.5  0.4  5.0       4.4  4.2\n",
       "8  2010     10.6  0.4  6.1       5.3  4.2\n",
       "9  2009      9.4  0.4  4.9       3.8  4.1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df9 = ts.get_gdp_pull()\n",
    "df9.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- year：统计年度\n",
    "- gdp_yoy：国内生产总值同比增长（%）(gdp_yoy = pi + si + ti)\n",
    "- pi：第一产业拉动率（%）；\n",
    "- si：第二产业拉动率（%）；\n",
    "- industry：其中工业拉动（%）；\n",
    "- ti：第三产业拉动率（%）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三大产业贡献率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>gdp_yoy</th>\n",
       "      <th>pi</th>\n",
       "      <th>si</th>\n",
       "      <th>industry</th>\n",
       "      <th>ti</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>36.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>35.7</td>\n",
       "      <td>31.9</td>\n",
       "      <td>59.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>38.2</td>\n",
       "      <td>30.7</td>\n",
       "      <td>57.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>42.5</td>\n",
       "      <td>35.4</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>47.9</td>\n",
       "      <td>39.2</td>\n",
       "      <td>47.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>48.5</td>\n",
       "      <td>40.5</td>\n",
       "      <td>47.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>100.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>41.9</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>45.9</td>\n",
       "      <td>43.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>57.4</td>\n",
       "      <td>49.6</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>52.3</td>\n",
       "      <td>40.7</td>\n",
       "      <td>43.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  gdp_yoy   pi    si  industry    ti\n",
       "0  2018    100.0  4.2  36.1       NaN  59.7\n",
       "1  2017    100.0  4.8  35.7      31.9  59.6\n",
       "2  2016    100.0  4.1  38.2      30.7  57.7\n",
       "3  2015    100.0  4.5  42.5      35.4  53.0\n",
       "4  2014    100.0  4.6  47.9      39.2  47.5\n",
       "5  2013    100.0  4.2  48.5      40.5  47.2\n",
       "6  2012    100.0  5.0  50.0      41.9  45.0\n",
       "7  2011    100.0  4.1  52.0      45.9  43.9\n",
       "8  2010    100.0  3.6  57.4      49.6  39.0\n",
       "9  2009    100.0  4.0  52.3      40.7  43.7"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df10 = ts.get_gdp_contrib()\n",
    "df10.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- year：统计年度\n",
    "- gdp_yoy：国内生产总值（%）(gdp_yoy = pi + si + ti)\n",
    "- pi：第一产业贡献率（%）；\n",
    "- si：第二产业贡献率（%）；\n",
    "- industry：其中工业贡献率（%）；\n",
    "- ti：第三产业贡献率（%）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 居民消费价格指数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>cpi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019.6</td>\n",
       "      <td>102.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019.5</td>\n",
       "      <td>102.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019.4</td>\n",
       "      <td>102.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019.3</td>\n",
       "      <td>102.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019.2</td>\n",
       "      <td>101.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019.1</td>\n",
       "      <td>101.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018.12</td>\n",
       "      <td>101.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018.11</td>\n",
       "      <td>102.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018.10</td>\n",
       "      <td>102.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018.9</td>\n",
       "      <td>102.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     month     cpi\n",
       "0   2019.6  102.68\n",
       "1   2019.5  102.74\n",
       "2   2019.4  102.54\n",
       "3   2019.3  102.28\n",
       "4   2019.2  101.49\n",
       "5   2019.1  101.74\n",
       "6  2018.12  101.86\n",
       "7  2018.11  102.18\n",
       "8  2018.10  102.54\n",
       "9   2018.9  102.50"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df11 = ts.get_cpi()\n",
    "df11.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- 统计月份\n",
    "- 价格指数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 工业品出厂价格指数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>ppiip</th>\n",
       "      <th>ppi</th>\n",
       "      <th>qm</th>\n",
       "      <th>rmi</th>\n",
       "      <th>pi</th>\n",
       "      <th>cg</th>\n",
       "      <th>food</th>\n",
       "      <th>clothing</th>\n",
       "      <th>roeu</th>\n",
       "      <th>dcg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019.6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>99.7</td>\n",
       "      <td>104.5</td>\n",
       "      <td>97.9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.9</td>\n",
       "      <td>102.2</td>\n",
       "      <td>101.6</td>\n",
       "      <td>100.5</td>\n",
       "      <td>99.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019.5</td>\n",
       "      <td>100.6</td>\n",
       "      <td>100.6</td>\n",
       "      <td>106.1</td>\n",
       "      <td>99.4</td>\n",
       "      <td>100.5</td>\n",
       "      <td>100.9</td>\n",
       "      <td>102.2</td>\n",
       "      <td>101.5</td>\n",
       "      <td>100.4</td>\n",
       "      <td>99.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019.4</td>\n",
       "      <td>100.9</td>\n",
       "      <td>100.9</td>\n",
       "      <td>105.3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.9</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.9</td>\n",
       "      <td>101.7</td>\n",
       "      <td>100.3</td>\n",
       "      <td>99.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019.3</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.3</td>\n",
       "      <td>104.2</td>\n",
       "      <td>99.4</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.5</td>\n",
       "      <td>101.2</td>\n",
       "      <td>101.7</td>\n",
       "      <td>100.3</td>\n",
       "      <td>99.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019.2</td>\n",
       "      <td>100.1</td>\n",
       "      <td>99.9</td>\n",
       "      <td>101.8</td>\n",
       "      <td>98.5</td>\n",
       "      <td>100.3</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.8</td>\n",
       "      <td>101.6</td>\n",
       "      <td>100.2</td>\n",
       "      <td>99.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019.1</td>\n",
       "      <td>100.1</td>\n",
       "      <td>99.9</td>\n",
       "      <td>101.2</td>\n",
       "      <td>98.4</td>\n",
       "      <td>100.3</td>\n",
       "      <td>100.6</td>\n",
       "      <td>100.8</td>\n",
       "      <td>101.6</td>\n",
       "      <td>100.3</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018.12</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.0</td>\n",
       "      <td>103.8</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.6</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018.11</td>\n",
       "      <td>102.7</td>\n",
       "      <td>103.3</td>\n",
       "      <td>109.2</td>\n",
       "      <td>104.6</td>\n",
       "      <td>102.2</td>\n",
       "      <td>100.8</td>\n",
       "      <td>101.1</td>\n",
       "      <td>101.5</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018.10</td>\n",
       "      <td>103.3</td>\n",
       "      <td>104.2</td>\n",
       "      <td>112.4</td>\n",
       "      <td>106.7</td>\n",
       "      <td>102.5</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.2</td>\n",
       "      <td>101.0</td>\n",
       "      <td>99.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018.9</td>\n",
       "      <td>103.6</td>\n",
       "      <td>104.6</td>\n",
       "      <td>111.7</td>\n",
       "      <td>107.3</td>\n",
       "      <td>102.9</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.1</td>\n",
       "      <td>101.1</td>\n",
       "      <td>100.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     month  ppiip    ppi     qm    rmi     pi     cg   food  clothing   roeu  \\\n",
       "0   2019.6  100.0   99.7  104.5   97.9  100.0  100.9  102.2     101.6  100.5   \n",
       "1   2019.5  100.6  100.6  106.1   99.4  100.5  100.9  102.2     101.5  100.4   \n",
       "2   2019.4  100.9  100.9  105.3  100.0  100.9  100.9  101.9     101.7  100.3   \n",
       "3   2019.3  100.4  100.3  104.2   99.4  100.4  100.5  101.2     101.7  100.3   \n",
       "4   2019.2  100.1   99.9  101.8   98.5  100.3  100.4  100.8     101.6  100.2   \n",
       "5   2019.1  100.1   99.9  101.2   98.4  100.3  100.6  100.8     101.6  100.3   \n",
       "6  2018.12  100.9  101.0  103.8  100.8  100.8  100.7  100.9     101.6  100.4   \n",
       "7  2018.11  102.7  103.3  109.2  104.6  102.2  100.8  101.1     101.5  100.8   \n",
       "8  2018.10  103.3  104.2  112.4  106.7  102.5  100.7  100.9     101.2  101.0   \n",
       "9   2018.9  103.6  104.6  111.7  107.3  102.9  100.8  100.9     101.1  101.1   \n",
       "\n",
       "     dcg  \n",
       "0   99.1  \n",
       "1   99.2  \n",
       "2   99.4  \n",
       "3   99.3  \n",
       "4   99.4  \n",
       "5  100.0  \n",
       "6  100.2  \n",
       "7  100.1  \n",
       "8   99.9  \n",
       "9  100.2  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "df12 = ts.get_ppi()\n",
    "df12.loc[0:9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回值说明：\n",
    "- month：统计月份\n",
    "- ppiip：工业品出厂价格指数\n",
    "- ppi：生产资料价格指数\n",
    "- qm：采掘工业价格指数\n",
    "- rmi：原材料工业价格指数\n",
    "- pi：加工工业价格指数\n",
    "- cg：生活资料价格指数\n",
    "- food：食品类价格指数\n",
    "- clothing：衣着类价格指数\n",
    "- roeu：一般日用品价格指数\n",
    "- dcg：耐用消费品价格指数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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